Both of these pruning techniques [1]}, [2]} pruned individual neurons from the network except that in the recent method [2]} L1 norm was used to prune away lighter weights. Although these methods pruned away a large number of weights from the network but they had a major shortcoming of introducing sparsity. More recent literature addressed this concern first by pruning filters as convolution operations constitutes the main computational burden of a CNN and second by using sparsity regularizers [4]}, [5]}, [6]}, [7]}, [8]}, [9]}, [10]}, [11]}, [12]}, [13]}, [14]}.
